Build and maintain data lake and data warehousing solutions for a B2B multi-tenant SaaS solution
Participate in the entire data pipeline lifecycle
Lead code and design reviews with junior and peer developers
Write clean code to develop data pipelines and necessary infrastructure as code
Monitor and troubleshoot performance, scalability, and security issues, making improvements as needed
Participate in the evaluation of new technologies and tools that can improve performance of our system
Participate in data governance process
Contribute to the design and documentation of our data lake platform
Gather technical and design requirements
Communicate effectively with technical and non-technical team members to ensure alignment and successful execution of projects

Typically requires a minimum of 5 years of related experience or 3 years and an advanced degree
Bachelor's degree in engineering, computer science, math, data engineering
Experience in the development of modern data architecture, analytics, data governance, AI/ML, or related areas
Experience with AWS big data technologies including EMR, Glue, S3, EKS, Lambda, Athena, RDS, MKS/Kafka/Kinesis
In-depth knowledge of the entire data engineering process (design, development, deployment)
Exposure with relational and NoSQL databases such as PostgresQL, Cassandra, DynamoDB, MongoDb etc and data modeling principles
Experience with DevOps, including CI/CD pipelines, containerized deployment/Kubernetes, and infrastructure-as-code/AWS Cloud Formation/Terraform
Proficient in SQL (SQL Server, Postgres) and Python
Ability to participate in on-call rotation
Strong experience with legacy data warehouse and ETL pipelines
Excellent analytical and time management skills, with a proven ability to deliver value independently
Strong written and verbal communication skills, with demonstrated experience providing technical input to technical and non-technical stakeholders

Senior Data Engineer

Key skills